The Polarization of Nationalist Cleavages and the 2016U.S. Presidential Election∗

Bart Bonikowski1, Yuval Feinstein2, and Sean Bock1

1Harvard University2University of Haifa

April 10, 2019

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Abstract: Research in political science has acknowledged the importance of ethno-nationalism (ormore commonly, nativism) as a constitutive element of radical-right politics, but it has typicallyreduced this phenomenon to its downstream correlates, like attitudes toward ethnic and religiousminorities or immigration policy preferences. Sociologists, on the other hand, have extensivelystudied nationalism as a feature of political culture, but have rarely weighed in on debates aboutinstitutional politics, and the radical-right in particular. In this study, we bring these literaturestogether by considering how multiple conceptions of American nationhood shaped respondents’voting preferences in the 2016 U.S. presidential election and how the election outcome built onlong-term changes in the distribution of nationalist beliefs in the U.S. population. The resultssuggest that competing definitions of nationhood constitute important cultural cleavages that wereeffectively mobilized by candidates from both parties. In particular, we show that exclusionaryvarieties of nationalism were strongly predictive of Trump support in the Republican primary andthe general election, while disengagement from the nation was predictive of Sanders support inthe Democratic primary. Furthermore, over the past twenty years, nationalism has become sortedby party: respondents identifying with the Republican Party have become predominantly ethno-nationalist, while those identifying with the Democratic Party have increasingly espoused creedaland disengaged conceptions of nationhood. The resulting mutual reinforcement of nationalist cleav-ages with other sources of cultural and demographic distinction represents a potential danger for thelong-term stability of U.S. democracy. More broadly, this research demonstrates that to understandthe 2016 presidential election—and contemporary American political culture—scholars should takenationalism seriously as a primary source of collective identification and political behavior.

∗Funding for this research was provided by the US-Israel Binational Science Foundation, the StanfordCenter for Advanced Study in the Behavioral Sciences, and the Harvard University Dean’s Fund for Innova-tion.

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1 Introduction

There is an emerging consensus in the politi-cal science and sociology literature that con-temporary radical-right politics—a categorythat subsumes most European right-wingparties, but also Donald Trump’s presiden-tial victory and the Brexit referendum—consists of three constitutive elements: pop-ulism, exclusionary nationalism, and au-thoritarianism (Bonikowski 2017; Mudde2007; Rooduijn 2014). While much recentresearch has explored the measurement andpolitical consequences of populist attitudes(Akkerman et al. 2014; Oliver and Rahn2016; Schulz et al. 2017; Van Hauwaertand Van Kessel 2018), the careful theo-rization and operationalization of national-ist beliefs has received comparably less at-tention, as has the study of the relation-ship between nationalism and political pref-erences. Instead, political scientists have fo-cused on down-stream attitudes that com-prise what they call “cultural” factors ex-plaining radical-right support. These in-clude xenophobia, racism, Islamophobia,anti-cosmopolitan backlash, and related be-liefs. In this paper, we address this gapin the literature by bringing insights fromcultural and political sociology to the studyof institutional politics. Specifically, we useoriginal survey data to inductively identifymultiple varieties of popular American na-tionalism and examine their relationship torespondents’ voting preferences in the 2016election. We then rely on repeated cross-sectional surveys of nationalist attitudes ad-ministered in 1996, 2004, 2012, and 2016to investigate whether long-term trends inthe distribution of nationalist beliefs, bothin the aggregate and across the two U.S. na-

tional parties, help explain Donald Trump’srise to political prominence.

Our analyses reveal that the four typesof American nationalism—creedal, restric-tive, ardent, and disengaged—identified inprevious research (Bonikowski and DiMag-gio 2016) were central to the 2016 presi-dential election. Even after controlling forsociodemographic covariates and partisanidentification, adherence to restrictive andardent nationalism was significantly predic-tive of endorsing Trump over the moder-ate candidates in the Republican primaryand of voting for Trump over Clinton inthe general election. In contrast, a disen-gaged disposition toward the nation—whichwe interpret as the absence of strong na-tionalist beliefs—was predictive of supportfor Sanders over Clinton in the Democraticprimary, but had no predictive power inthe general election. These associations areplaced into further relief by a striking find-ing from our longitudinal analysis: whileexclusionary forms of nationalism have notbeen on the rise in the U.S. population (in-deed, strong forms of nationalism in gen-eral have been giving way to disengagementfrom the nation), there is strong evidence ofpersistent partisan sorting of nationalist be-liefs over the past two decades. Whereasthe four varieties of nationalism had cutacross partisan identification in 1996, by2016, respondents identifying with the Re-publican Party had become predominantlyethno-nationalist, while a large majority ofthose identifying with the Democratic Partyhad come to see the nation in inclusiveterms.

These results point to the central roleplayed by nationalist beliefs in the 2016election, and in contemporary U.S. poli-tics more broadly. Differences in popu-

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lar conceptions of nationhood appear tohave transformed over time from latent cul-tural cleavages—correlated with political at-titudes but not primarily driving politicalbehavior—to active political cleavages thathave been effectively mobilized by recentpresidential campaigns, most successfullyso by Donald Trump’s persistently ethno-nationalist appeals. Moreover, while na-tionalist beliefs are not reducible to par-tisanship (as evidenced by the persistentmarginal effects of nationalism in our sta-tistical models), the increasing correlationbetween these two types of identities islikely to reinforce other sociodemographicand ideological cleavages, potentially lead-ing to greater negative partisanship andlower probability of political compromise inthe coming years (Manza and Brooks 1999;Rokkan and Lipset 1967).

2 ”Cultural” Sources of

Radical-Right Support

Political science explanations—as well asmedia accounts—of popular support forradical-right parties tend to fall into twocategories: those stressing economic factors,such as exposure to financial crises, incomeinequality, deindustrialization-driven unem-ployment, trade shocks, or the redistribu-tive consequences of capital mobility, andthose emphasizing ”cultural” factors, suchas racism, xenophobia, Islamophobia, or abacklash against cosmopolitanism (Golder2016).1 Economic explanations claim that

a range of structural shocks have gener-ated a growing sense of precariousness in lo-cal communities, particularly among whiteworking-class individuals residing outside ofmajor urban centers, and that the result-ing economic anxiety has led these votersto favor anti-establishment candidates onthe radical right. Right-wing politicianshave effectively mobilized economic discon-tent through their vocal opposition to eco-nomic globalization and their moral vilifica-tion of liberal elites, as well as immigrantsand minorities. The latter in particular havebeen portrayed as recipients of unfair advan-tages in access to jobs, educational institu-tions, and welfare state programs.

In contrast, what political scientists referto as ”cultural” explanations focus on theprimary role of out-group stigmatization indriving radical-right support. This perspec-tive rests on the claim that economic anxietyis neither a necessary nor sufficient cause ofvoters’ favorability toward candidates whocapitalize on out-group antipathies. In-stead, it is voters’ deep-seated racism andxenophobia—or at the very least, a generaldistaste for multicultural and cosmopoli-tan cultural norms (Norris and Inglehart2018)—that gives resonance to such cam-paign messages. In addition to furnish-ing correlations between the relevant atti-tudes and radical-right support, those favor-ing cultural explanations often point to theweaknesses of the economic framework: thatradical-right supporters tend not to be theworst off in society, that they often opposeeconomic redistribution (especially if it in-volves benefits for the groups they dislike),

1In addition to explaining the demand side of radical-right politics, political scientists stress the impor-tance of institutional mechanisms, such as changes in candidate selection processes and the weakening ofparty organizations, as well as the impact on public opinion of the rise of social media and the growth of par-tisan cable news (Golder 2016). We bracket these factors, because our interest is primarily in individual-levelcorrelates of political behavior.

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and that racial segregation is a more typi-cal characteristic of the areas in which thesevoters live than is having borne the brunt ofeconomic decline.

Increasingly, the evidence, in both Eu-rope and the United States, appears tofavor cultural explanations of radical-rightsupport (Mutz 2018b; Sides et al. 2018).Nonetheless, the economy-culture debatesuffers from two fundamental problems.First, its central dichotomy is misplaced(Gidron and Hall 2017), because it ignoresthe fact that culture shapes economic per-ceptions (e.g., sociotropic economic con-cerns can be based not only on personal ex-perience but also perceptions of how peo-ple in one’s reference group are faring com-pared to those in perceived out-groups [Cit-rin et al. 1997; Hochschild 2018:137–140])and that economic anxieties are themselvesmediated by cultural frames (e.g., it is onlythose economic shocks that are perceivedas unfair that tend to activate radical-right support [Rodrik 2018]). Second, andmore relevant for our purposes, the de-bate subsumes under “culture” a wide rangeof attitudes—including xenophobia, racism,Islamophobia, and anti-cosmopolitanism—without specifying the cultural mechanismsthat connect them (but see Jardina 2019;Mason 2018). While these phenomena areeasily operationalized, they are theoreticallythin and analytically inadequate, not leastbecause they are able to explain radical-right support only in some contexts but notothers. For instance, Islamophobia is usefulfor understanding the successes of the FrontNational in France, but xenophobia againstPolish immigrants is more relevant for mak-ing sense of the Brexit referendum in theUnited Kingdom. In the U.S. case, the vili-fication of Mexican migrants was centrally

important to the Trump campaign whileovert racial claims were largely absent fromit (Lamont et al. 2017), and yet, both racismand anti-immigrant sentiments were highlypredictive of a people’s decision to vote forTrump (Sides et al. 2018).

One way in which some scholars havesought to bridge these distinct phenom-ena is to subsume them under the cate-gory of nativism: the principle ”that statesshould be inhabited exclusively by mem-bers of the native group (‘the nation’) andthat nonnative elements (persons and ideas)are fundamentally threatening to the ho-mogenous nation-state” (Mudde 2007:19).This is a more promising analytical cate-gory than ”culture” writ large, because itplaces emphasis on definitions of legitimatemembership in the nation, which are coreto people’s collective identities. Nativism,however, is less flexible than our preferredterm, ethno-nationalism (Bonikowski 2017;Manza and Crowley 2018). The latter isone among multiple possible varieties of na-tional self-understanding, which allows formeaningful comparisons across alternativebelief systems, and it is less directly asso-ciated with anti-immigrant sentiments (cf.Higham 1955)—it subsumes them but is notlimited to them. Finally, nationalism isrooted in a rich tradition of research on therise of the modern-nation state and the ide-ologies that legitimize it as a primary ob-ject of popular identification and loyalty.These include criteria of legitimate mem-bership in the nation, but also other rele-vant aspects of nationhood, such as domain-specific national pride and perceptions ofnational superiority. Together, these beliefsconstitute people’s cultural schemas of thenation, which have important implicationsfor their political preferences and are empir-

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ically tractable using survey data. Bring-ing these phenomena to bear on DonaldTrump’s election, an important case of con-temporary radical-right politics, is the pri-mary objective of this study.

3 Nationalist Cleavages

in the United States

In his influential book Civic Ideals, RogersSmith (1997) demonstrates that Americannational identity has never been character-ized by singular adherence to the liberalvalues of the American Creed. Instead, ithas vacillated between sharply distinct andcompeting belief systems (liberalism, butalso republicanism and white supremacy),the residues of which Smith painstakinglytraces across the patchwork of U.S. citizen-ship law. The notion that conceptions of na-tionhood are heterogeneous within countrieshas also motivated survey researchers, whohave shown that similar distinctions to thoseobserved in archival data are found in publicopinion, and that these beliefs are stronglyassociated with key policy preferences (Cit-rin et al. 2001; Theiss-Morse 2009; Schild-kraut 2010). More recently, Bonikowskiand DiMaggio (2016) used inductive surveyanalysis methods to identify four distinctschemas of American nationhood: creedal,restrictive, ardent, and disengaged. Theirfindings differed from past studies in fourimportant ways: (1) they were based on awide range of items that tapped criteria ofnational membership, national pride, chau-vinism, and the strength of national attach-ment; (2) instead of aggregating variables(as in factor analysis, for instance), theyclustered respondents based on the latter’s

shared beliefs; and (3) they demonstratedthat the resulting configurations of nation-alist attitudes were not only patterned andcorrelated with political preferences, butalso large invariant in their composition overtime.

Bonikowski and DiMaggio’s (2016) re-sults suggest that the four types of na-tionalism identified in their study can bethought of as stable cultural cleavages inthe U.S. population, which function asthe public-opinion counterparts (with somevariations) to the policymaking traditionsdocumented by Smith (1997). These cleav-ages are likely to be latent during set-tled historical times, operating largely inthe cultural background. Under such cir-cumstances, nationalist beliefs may mani-fest themselves in micro-interactions, as ei-ther sources of in-group cohesion or inter-group animosity, but not as primary fea-tures of electoral campaigns or voting be-havior (though their downstream policy cor-relates may well be more salient). Occa-sionally, however, a confluence of structuralconditions may bring disputes about the na-tion’s meaning to the forefront of politi-cal claims-making and individual-level po-litical preferences (Bonikowski 2017). Giventhe prominence of anti-minority discourse incontemporary radical-right politics, the cur-rent era appears to represent precisely thiskind of conjuncture.

Following these insights, our paper ex-amines whether nationalist beliefs were sig-nificantly associated with presidential can-didate preferences in the 2016 election (cf.Manza and Crowley 2018), a watershed forexclusionary politics in the United States,and if so, whether this outcome was pre-ceded by a shift in the distribution of ethno-nationalist beliefs in the U.S. population

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over the prior two decades. Our inter-est in the former questions is prompted bythe widespread reliance of 2016 presidentialcandidates on multiple types of nationalistrhetoric. Donald Trump is the most obvi-ous example. His primary and general cam-paigns escalated racial fear-mongering tolevels not seen in decades, by unabashedlyportraying Mexican migrants as immoraland dangerous, Mexican-Americans as un-American, and Muslim refugees as nationalsecurity threats. This rhetoric emergedout of Trump’s earlier championing of the”birther” movement, which questioned thelegitimacy of President Barack Obama as anelected official and an American. Againstthis backdrop, Trump’s persistent appealsto white working and middle class Ameri-cans had a decidedly white nationalist un-dertone, only further reinforced by his re-fusal to disavow the support of extremistmovement leaders like former KKK GrandWizard David Duke (Lamont et al. 2017).Donal Trump was not, however, the onlyRepublican to make such claims. Ted Cruz,though less explicit, was eager to competewith Trump on the latter’s terms, frequentlysignaling his toughness on immigration andhis national security bona fides. The re-maining candidates for the Republican nom-ination either downplayed nationalism alto-gether or relied on boilerplate patriotic im-agery typical of creedal nationalism.

On the Democratic side, Hillary Clin-ton’s campaign was more centrally con-cerned with policy proposals than identi-tarian appeals, but when she did referencenationalist claims and imagery, she did soin a decidedly civic nationalist register, de-picting America as an exceptional imaginedcommunity whose egalitarian ideals and hu-man achievements are deserving of deep na-

tional pride. These themes were featuredespecially prominently in the DemocraticNational Convention, the overtly patrioticpageantry of which bore striking resem-blance to traditional Republican campaigns.In contrast to Clinton, her chief rival in theprimary election, Bernie Sanders, eschewednationalism altogether, focusing instead ona broadly populist economic message.

To ensure that our characterization ofthe content of the 2016 election campaigns isaccurate, we perform a descriptive analysisof the candidates’ campaign speeches. Thedata were obtained from two online sources:Factba.se, a database of all public state-ments made by Donald Trump over his life-time, and the American Presidency Projectat the University of California, Santa Bar-bara, a compendium of political statementsby prominent U.S. politicians, which weuse a source of Hillary Clinton’s, BernieSanders’, Ted Cruz’s, and the moderate Re-publicans’ campaign discourse. We limit ourcorpus to speeches delivered during the 2016primary and general elections, beginningwith each candidate’s presidential run an-nouncement and ending with his or her con-cession speech. After scraping and cleaningthe speech transcripts, we use a word em-bedding model (specifically word2vec) andTensorflow visualization to examine differ-ences in the meaning of key terms relevantto our research question between the cam-paigns.

Word embedding models use shallowneural networks to arrive at a representa-tion of each word in a corpus as a densek-dimensional vector, such that distance be-tween words in the resulting k-dimensionalspace is indicative of the proximity of thewords to one another in the corpus (the al-gorithm arrives at the solution by predict-

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ing the probability of each word’s occur-rence given the co-presence of its neighbor-ing words) (Mikolov et al. 2013). One ofthe many advantages of this method is thatit allows for the visualization of a word’smeaning in a given corpus (assuming thatmeaning emerges out of the relations of simi-larity and difference between symbols [Mohr1998]). We take advantage of this feature tocompare the meanings of key words acrossmultiple 50-dimensional vector spaces gen-erated by the campaign-specific text cor-pora. Data collection and analysis was per-formed in Python using a variety of webscraping and text analysis packages, includ-ing scrapy and gensim.

To highlight differences in the cam-paigns’ rhetoric, we focus on the candidate-specific meanings of two terms: ’danger-ous’ and ’politics.’ The former illustrateswhat the candidate views as the most press-ing concerns facing the country (e.g., cli-mate change, terrorism, immigrants) and,given the word’s potency, is likely to elicitmorally charged content typical of nation-alist discourse. The latter term may re-veal whether or not the candidate framesthe political establishment in morally nega-tive terms, which may activate varieties ofnationalism that score low on institutionalpride (i.e., restrictive nationalism and disen-gagement from the nation). Figures 1 and 2use a two-dimensional mapping of the vectorspace to visualize the 50 word vectors mostproximate to each of the two key terms, re-spectively, across the multiple campaigns.Due to the small number of speeches bymoderate Republican primary candidates,we group them into a single corpus. [Pleasenote: in this draft of the paper, we only in-clude the figures for Clinton and Trump.]

The results of the word embedding anal-

ysis are broadly consistent with our earliercharacterization of the campaigns. Don-ald Trump’s discourse stands out in itsalarmist conflation of ’aliens’ and ’refugees’(as well as ’somali’ and ’overstay [presum-ably a visa]’) with ’gangs,’ ’cartels,’ ’terror-ist[s],’ ’kingpins,’ and other types of criminalactivity. This pains a picture of America asa nation under siege by dangerous outsiders.This is combined with an acrimonious viewof politics as characterized by the ’failures’and ’hypocrisy’ of ’corrupt’ and ’arrogant’’establishment’ ’elites,’ who have ’failed’ thepeople.

Clinton’s claims about the problems fac-ing America are starkly different. Ratherthan fo cusing on specific groups of peopleand their alleged threatening deeds, she fo-cuses on the dangers posed by ’prejudice,’’discrimination,’ ’bullying,’ and ’partisan-ship.’ Her view of politics is largely positive,as indicated by terms such as ’optimistic,’’inspire,’ ’obligation,’ ’diversity,’ and ’bipar-tisan.’ To the degree that politics is ’bro-ken,’ it is due to its ’partisanship,’ not anyattribute of the elites.

Whereas the Republican moderates aresimilar in their depictions of danger and pol-itics to Clinton, the same cannot be said ofSanders or Cruz. Sanders’ speeches lack anydiscussion of immigrants or minorities, in-stead focusing on the dangers posed by ne-oliberalism and growing economic inequal-ity, but his depiction of politics shares muchin common with Trump’s. Cruz’s discourse,on the other hand, identified similar dangersto Trump’s (though with a stronger focus onterrorism than immigration, which is consis-tent with his intended appeals to Latinos)and depicted politics in a similarly negativelight to that of Trump and Sanders.

In light of these supply-side patterns,

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Figure 2: Word embedding results: 50 most proximate word vectors to ”politics”

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we can generate some broad expectationsfor the survey data analysis. We dividethese between those concerning voters’ pref-erences in the Republican and Democraticprimaries and those specific to the generalelection. Given the strength of partisanidentification in the United States and theresulting prevalence of party-line voting, thequestion of why Donal Trump won the elec-tion is actually less interesting than why hewas able to capture his party’s nominationin the first place. Nonetheless, national-ism may have played a role, albeit a smallerone, in the final Clinton vs. Trump con-test as well. In general, we expect DonaldTrump’s supporters to be particularly likelyto espouse forms of nationalism that privi-lege ethnoculturally exclusionary criteria ofnational membership (Manza and Crowley2018). Among those, we may find both re-strictive nationalists, who score relativelylow on measures of national pride (in linewith Trump’s own pessimistic view of con-temporary American society), and ardentnationalists, whose jingoism is more in linewith traditional Republican beliefs. Clin-ton’s supporters in the general election, onthe other hand, should be more likely to es-pouse either creedal nationalism that is highin national pride but favors inclusive criteriaof national belonging or general disengage-ment from the nation. Hence the followingtwo hypotheses:

Hypothesis 1 (H1): In the generalelection, support for Trump, as opposed toClinton, was significantly associated withadherence to restrictive and ardent nation-alism. This relationship should hold evenafter controlling for partisan identification.

Hypothesis 2 (H2): In the generalelection, support for Clinton, as opposed toTrump, was significantly associated with ad-

herence to creedal and disengaged disposi-tions toward the nation. This relationshipshould hold even after controlling for parti-san identification.

In the primaries, we should observe littledifference in the nationalist beliefs of Trumpand Cruz supporters, given that both candi-dates engaged in persistent appeals to eth-nocultural exclusion and nationalist nostal-gia. The supporters of mainstream can-didates, like John Kasich, Jeb Bush, andMarco Rubio, however, should be less likelyto adhere to exclusionary forms of national-ism and more likely to favor a creedal defi-nition of nationhood (in line with the cam-paign speech analysis). For Democratic can-didates, the main difference between Clin-ton and Sanders supporters should consistof endorsement or rejection of affirmativenationalism, respectively, with Sanders sup-porters more likely to be disengaged fromthe nation. Sanders’ use of populist rhetoricmay have found appeal among this group aswell, given their low level of pride in boththe nation and the state. This leads to thefollowing three hypotheses:

Hypothesis 3 (H3): In the Republicanprimary election, support for Trump, as op-posed to the mainstream candidates, shouldbe significantly associated with adherence torestrictive and ardent nationalism.

Hypothesis 4 (H4): In the Republi-can primary election, there should be no sig-nificant differences in nationalist beliefs be-tween Trump and Cruz supporters.

Hypothesis 5 (H5): In the Democraticprimary election, support for Sanders, asopposed to Clinton, should be significantlyassociated with disengagement toward thenation.

If the tests of the above hypotheses con-firm that nationalist beliefs played an im-

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portant role in the 2016 election, this raisesthe question of what led to nationalism’s risein prominence at this historical juncture.While many reasonable structural and insti-tutional explanations have been suggested—and a complete account is likely to bemulticausal—we focus specifically on long-term trends in the distribution of national-ist beliefs in the United States, because suchbeliefs provide a fertile soil within whichradical politics can take root. Using dataspanning two decades between 1996 and2016, we evaluate two possible causal pre-conditions for nationalism’s newfound rele-vance: an aggregate increase in exclusionarynationalism in the U.S. population, whichwould have increased the overall demand forradical-right politics, and the partisan sort-ing of exclusionary nationalist beliefs, whichwould have made nationalism more salientwithin each party. Although both of thesetrends could have developed simultaneously,prior research suggests that changes to therelative salience of ethno-nationalism maybe more relevant than changes in its aggre-gate prevalence (Bonikowski 2017; Hatton2017; Levitsky and Ziblatt 2018; Rydgren2003). Moreover, the partisan sorting of awide range of policy attitudes has been amajor trend in U.S. politics over the pastthirty years (Baldassarri and Gelman 2008),so there is good reason to expect national-ism to follow suit. This leads to our finaltwo hypotheses:

Hypothesis 6 (H6): Restrictive andardent nationalism increased in prevalencebetween 1996 and 2016, reaching a peakprior to the 2016 election.

Hypothesis 7 (H7): Restrictive andardent nationalism became more closely as-sociated with Republican partisan identifica-tion between 1996 and 2016, while creedal

nationalism and disengagement from the na-tion became more closely associated withDemocratic partisan identification between1996 and 2016.

4 Data

The main data used for the cross-sectionalanalysis of the 2016 election were collectedby YouGov on November 5-6, the weekendbefore Election Day, as part of a larger com-parative survey on nationalism funded bythe U.S.-Israeli Binational Science Founda-tion. The sample was drawn from YouGov’spanel using Census-based quotas and thenmatched to the U.S. non-institutionalizedpopulation using post-stratification weight-ing. The final sample consists of 956 respon-dents.

The survey asked respondents a widerange of questions about their collectiveidentities, social attitudes, and politicalpreferences. Our study focuses in particu-lar on a battery of twenty-six items measur-ing multiple aspects of popular nationalism,including strength of national attachment,criteria of legitimate membership in the na-tion, domain-specific national pride, andchauvinism. This battery was directly mod-eled on questions from the General SocialSurvey—collected under the auspices theInternational Social Survey Programme—which have been the subject of numerousscholarly studies (e.g., Huddy and Khatib2007; Kunovich 2009; Wright 2011). Mostrecently, these GSS data were used byBonikowski and DiMaggio (2016) to con-struct the same four types of nationalismused as independent variables in our hy-potheses.

Our main dependent variables are vot-

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ing preferences in the 2016 primary and gen-eral elections. The fact that the data werecollected only a couple of days before Elec-tion Day allows us to obtain reliable mea-sures of vote intention, in line with bestpractices in political science (Atkeson 1999;Mutz 2018a). Data on primary vote choicesare based on retrospective accounts and aretherefore susceptible to bias in favor of theprimary winner. Given that our main in-terest, however, is in how ethno-nationalistbeliefs shaped Trump support, the overesti-mation of Trump primary votes should makeour results more conservative.2

For the longitudinal analysis (H6 andH7), we rely on a unique dataset of nation-ally representative repeated cross-sectionalsurveys that feature a consistent set of na-tionalism items. We compile these fromthe 1996 and 2004 General Social Surveys,a 2012 GfK Custom Research Survey fea-tured in Bonikowski and DiMaggio (2016),and the 2016 YouGov data used for ourcross-sectional analyses. To the best of ourknowledge, this is the most complete timeseries of Americans’ nationalist beliefs everused in social science research. The datacover a period of important developments inU.S. politics—including rising polarization,growth in executive power, the September11, 2001 attacks, and the Great Recession—spanning the Clinton, Bush, and Obamapresidencies. The weighted descriptivestatistics for the five waves of data areshown in Table 1.

5 Methods

To identify varieties of American nation-alism, we use latent class analysis (LCA),a data reduction method that groups ob-servations based on their shared responsepatterns across multiple indicators. Wedo so both for theoretical reasons—becausewe view this relational and inductive ap-proach as most appropriate for measuringdomain-specific cognitive representations,and those of the nation in particular—andfor practical reasons—because this was themethod used in past research (Bonikowskiand DiMaggio 2016) to segment national-ist beliefs in the U.S. population and theresulting classification scheme informed ourhypotheses. For three of the four waves ofdata (1996, 2004, and 2012), our use of LCAamounts to an independent in-sample repli-cation of Bonikowski and DiMaggio’s (2016)descriptive results, but for the remainingwave (2016), it is an empirical questionwhether the same four nationalism typesemerge out of the data.

The LCA models in all of our analy-ses are partially homogeneous; that is, theposterior distribution of the latent classesin the sample is allowed to vary, but thecomposition of the classes (i.e., the posteriorprobability of a particular response to eachnationalism indicator within each class) isfixed. We employ this strategy in order toenable meaningful comparisons over time.As a robustness check, we also estimate fullyheterogeneous models and examine the sta-bility of the class composition across thefour waves of data. In both the partially

2Under the null hypothesis of no relationship between nationalism and primary vote, the retrospectiveoverestimation of Trump support should make little difference, while under the alternative hypothesis, itshould have a downward bias on the ethno-nationalism coefficients, by conflating true ethno-nationalistTrump supporters with false-recall supporters who did not espouse ethno-nationalist beliefs.

11

Table 1: Descriptive Statistics for Four Waves of Nationalism Survey Data

1996 2004 2012 2016

Not Born in US 955 916 — 782Mean 0.08 0.10 — 0.28SD 0.27 0.30 — 0.45

Age 953 916 2341 782Mean 43.20 44.61 51.20 45.73SD 16.19 16.01 16.46 17.43

Male 956 916 2341 782Mean 0.50 0.47 0.51 0.48SD 0.50 0.50 0.50 0.50

Party IDStrong Democrat 937 905 2183 754

Mean 0.14 0.16 0.21 0.20SD 0.35 0.37 0.41 0.40

Democrat 937 905 2183 754Mean 0.32 0.28 0.21 0.24SD 0.47 0.45 0.41 0.42

Independent 937 905 2183 754Mean 0.13 0.13 0.17 0.23SD 0.34 0.34 0.38 0.42

Republican 937 905 2183 754Mean 0.29 0.26 0.21 0.21SD 0.45 0.44 0.41 0.41

Strong Republican 937 905 2183 754Mean 0.12 0.16 0.20 0.13SD 0.33 0.37 0.40 0.34

RaceWhite 956 916 2341 782

Mean 0.83 0.78 0.77 0.65SD 0.38 0.42 0.42 0.48

Black 956 916 2341 782Mean 0.09 0.12 0.07 0.12SD 0.29 0.32 0.26 0.33

Hispanic 956 916 2341 782Mean 0.04 0.06 0.10 0.16SD 0.20 0.24 0.29 0.37

Other 956 916 2341 782

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Table 1 - continued from previous page

1996 2004 2012 2016

Mean 0.04 0.05 0.06 0.07SD 0.19 0.22 0.23 0.26

RegionNorth East 956 916 2341 782

Mean 0.20 0.19 0.18 0.18SD 0.40 0.39 0.39 0.38

Midwest 956 916 2341 782Mean 0.24 0.25 0.24 0.21SD 0.42 0.43 0.43 0.41

South 956 916 2341 782Mean 0.31 0.33 0.34 0.37SD 0.46 0.47 0.47 0.48

Mountatin 956 916 2341 782Mean 0.09 0.07 0.07 0.08SD 0.28 0.26 0.25 0.27

Pacific 956 916 2341 782Mean 0.16 0.16 0.16 0.16SD 0.37 0.36 0.37 0.36

EducationLess than HS 956 916 2341 782

Mean 0.13 0.10 0.07 0.08SD 0.33 0.29 0.25 0.27

HS or Some College 956 916 2341 782Mean 0.58 0.56 0.59 0.68SD 0.49 0.50 0.49 0.47

Bachelor’s Degree 956 916 2341 782Mean 0.16 0.20 0.20 0.16SD 0.36 0.40 0.40 0.37

Advanced Degree 956 916 2341 782Mean 0.14 0.14 0.14 0.08SD 0.35 0.34 0.35 0.28

Religious TraditionProtestant 956 916 2135 782

Mean 0.53 0.45 0.41 0.24SD 0.50 0.50 0.49 0.43

Roman Catholic 956 916 2135 782Mean 0.26 0.27 0.27 0.26

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Table 1 - continued from previous page

1996 2004 2012 2016

SD 0.44 0.44 0.44 0.44

Jewish 956 916 2135 782Mean 0.02 0.03 0.02 0.01SD 0.12 0.17 0.15 0.11

Other 956 916 2135 782Mean 0.09 0.12 0.11 0.19SD 0.28 0.33 0.31 0.39

None 956 916 2135 782Mean 0.11 0.13 0.19 0.29SD 0.31 0.33 0.40 0.46

Religiosity 918 910 2267 782Mean 0.36 0.39 0.43 0.41SD 0.48 0.49 0.50 0.49

homogeneous and fully heterogeneousmodels, we rely on statistical goodness offit and interpretive criteria to select the ap-propriate number of classes. As in paststudies, a four-class solution provides thebest compromise between precision and in-terpretability (besides not offering an ad-vantage in model fit, the addition of a fifthclass does not add theoretically meaningfulinformation to the analysis). For more de-tails about model selection, see Appendix A.Once we identify the four types of national-ism in the data, we regress on them respon-dents’ vote preferences in the primary andgeneral elections using logistic regression.

6 Results

6.1 Varieties of American Na-tionalism

The LCA analysis yields four types of na-tionalist beliefs, summarized in Figure 3.

Following Bonikowski and DiMaggio (2016),we label them creedal, restrictive, ardent,and disengaged. Creedal nationalists fa-vor elective criteria of national belonging—rating subjective identification with the na-tion and respect for American laws and in-stitutions as very important—while beingmore equivocal than others about impor-tance of life-long residence and languageskills, and viewing birth in the country, hav-ing American ancestry, and being Christianas not very important. They display mod-erate levels of national pride (with pride inAmerica’s scientific accomplishments rank-ing highest and pride in its social securitysystem ranking lowest) and low levels ofchauvinism (e.g., only 24 percent agree thatthe world would be a better place if oth-ers were more like Americans). This re-sponse pattern is broadly consistent withthe central tenets of the American liberalcreed (Lipset 1967).

Restrictive and ardent nationalists en-dorse both elective and ascriptive criteria of

14

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Figure 3: Posterior Probabilities of Nationalist Item Responses by Latent Class

15

national belonging, rating them all as veryimportant (with the importance of Chris-tian faith ranking lowest, endorsed by 71percent of ardents and 84 percent of re-strictives). The two classes differ, however,in their degree of pride in America’s ac-complishments and their evaluation of thecountry’s relative standing in the world.Restrictive nationalists exhibit considerablylower levels of pride than ardent nation-alists and these differences are most pro-nounced for questions related to nationalinstitutions, such as pride in the way thecountry’s democracy works (with 13 percentof restrictives expressing strong pride com-pared to 71 percent of ardents), its politicalinfluence in the world (8 vs. 55 percent),and its economic achievements (13 vs. 76percent). With respect to chauvinist atti-tudes, restrictives are also less effusive intheir celebration of American exceptional-ism than ardents, with, for instance, only39 percent of the former, compared to 72 ofthe latter, strongly agreeing that America isbetter than most countries, and 45 percentof the former, compared to 61 percent of thelatter, strongly endorsing the idea that theworld would be a better place if others weremore like Americans.

For restrictive nationalists, unlike ardentnationalists, then, high barriers to nationalmembership are accompanied by muted af-fect toward the nation—and the state—atleast in its contemporary form. The factthat pride in America’s history is an excep-tion to this pattern suggests that restrictivenationalists may espouse a sense of nostal-gia for a (real or imagined) bygone America,one that is at odds with contemporary so-cial and cultural changes. If so, this wouldplace their beliefs squarely in line with the

alarmist rhetoric of the Trump campaignand administration. At the same time, theexclusionary and chauvinistic beliefs of theardent nationalists are likely to have at-tracted them to the Trump message as well.

Finally, the disengaged class is charac-terized by an arm’s length relationship tothe nation. Respondents in this group donot view any criteria of national member-ship as particularly important, they are notespecially proud of any aspect of Americannationhood, and they do not view Amer-ica as exceptional or superior compared toother countries. While we hesitate to go sofar as to label these respondents as ”non-nationalist” or ”post-nationalist,” it doesappear that for them, the national frame ofreference is not particularly salient. Giventhese characteristics, the absence of overtnationalism in Bernie Sanders’ campaignmay have held particularly strong appeal forthese respondents.3

6.2 Nationalism in the 2016Election

The four types of nationalism successfullyreplicated in our data have been shown tobe significantly associated with social at-titudes and policy preferences, but no re-search has examined their implications forelectoral politics. This is the analysis towhich we turn next. Having generated thelatent classes and assigned respondents toeach using modal assignment based on pos-terior membership probabilities, we regressself-reported voting preferences on class as-signment. We do so using stepwise logisticregression, beginning with a baseline model,then adding respondents’ sociodemographic

3Of course, they may have also supported other candidates based on issues distinct from national identity.

16

attributes (birth in the U.S., age, gender,race, geographic region, income, education,and religion) in the second model, and par-tisan identification in the third model (weinclude partisanship only in the general elec-tion analyses). All analyses were carried outin the LatentGOLD 5.1 software packageusing a three-step model with a maximumlikelihood adjustment for classification bias(Bakk et al. 2013). For ease of interpreta-tion, we present only the nationalism coeffi-cients in a series of figures, but the completeregression results are available in AppendixC.

The results of the general election mod-els are presented in the first panel of Fig-ure 4. Consistent with our expectations,in the baseline model, creedal nationalismand disengagement from the nation are bothnegatively associated with Trump support,compared to support for Hillary Clinton,whereas restrictive and ardent nationalismare positively associated with Trump sup-port. These results are consistent with Hy-potheses 1 and 2: Trump’s campaign dis-course activated exclusionary varieties of na-tionalism among the American public.

Inclusion vs. exclusion, however, is notthe only axis of variation driving the associ-ation between nationalism and voting pref-erences in the general election. Among thetwo types of exclusionary nationalism, re-strictive nationalism, characterized by rela-tively low pride in the nation-state is signif-icantly more predictive of Trump supportthan is ardent nationalism, which featureshigh levels of national pride. A similar pat-tern is found among the inclusive classes:disengagement from the nation is signifi-cantly more predictive of Trump supportthan is creedal nationalism. It appears then

that the appeal of radical-right discourse isnot limited to claims based on ascriptive in-group identity and out-group hostility: lowlevels of national pride (and chauvinism)are also likely to be activated by populistcritiques of political elites and institutionsand the nostalgic glorification of the nation’spast. These motifs featured prominently inour earlier analyses of Trump’s (but alsoSanders’) campaign speeches.

Controlling for respondents’ sociode-mographic characteristics in the secondgeneral-election model does not have a ma-jor impact on the magnitude or significanceof the coefficients comparing creedal nation-alism with the other three latent classes:nationalist exclusion and low levels of na-tional pride continue to predict Trump sup-port. The differences among ardent, restric-tive, and disengaged classes, however, areno longer significant. This is primarily a re-sult of controlling for race (Trump supportis lower among African Americans and Lati-nos), religion (Catholics, Jews, and the non-religious are more favorable of Clinton), ed-ucation (Trump supporters are most likelyto have a high school diploma or some col-lege), and income (which is positively asso-ciated with Trump support).4

The final model predicting Trump sup-port in the general election introduces par-tisan identification as an additional covari-ate. Although we predicted that national-ism would continue to have net effects ofcandidate preferences in this model (see H1and H2), there is good reason to expect theopposite as well. As suggested by the lit-erature on partisan polarization, motivatedreasoning, and negative partisanship (for arecent synthesis see Mason (2018)), partisanidentity typically outweighs all other predic-

4The income and education results are consistent with Manza and Crowley (2017).

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Figure 4: Logistic Regression of General Election Vote Preferences on Nationalist Attitudes,Trump vs. Clinton

18

tors of vote choice in U.S. presidential elec-tions. Once candidates are chosen by theparties, Republicans are likely to vote fora Republican and Democrats for a Demo-crat, regardless of who is at the top of eachticket (Bartels 2016). Yet, despite this com-mon finding, our results provide evidencefor the persistent relevance of nationalism inthe 2016 election. The party coefficients arelarge and highly significant (see AppendixC), but the ardent, restrictive, and disen-gaged classes (when compared to creedalnationalism) continue to be predictive ofTrump support net of partisan identifica-tion.

We now turn to the two party primaries.The second panel of Figure 4 presents re-sults for the Republican race, comparingTrump support with support for the moder-ate candidates (i.e., John Kasich, Jeb Bush,and Marco Rubio). Compared to creedalnationalism, restrictive and ardent national-ism are consistently associated with greatersupport for Trump over his moderate rivals,whereas the difference between restrictiveand ardent nationalism is not significant.The coefficients comparing disengagementfrom the nation to ardent and restrictive na-tionalism are negative as well, but they failto reach statistical significance. There areno major differences between the baselinemodel and a model that includes sociode-mographic covariates.

These results provide partial evidencefor Hypothesis 3: respondents who favoran inclusive definition of the nation aremore likely to support moderate Republi-can candidates, but only when such beliefsare accompanied by strong national pride(as in the creedal class). This suggests that,

ethno-nationalism—a feature of both re-strictive and ardent nationalism—and lowersatisfaction with the nation-state—a featureof the disengaged class—were important fac-tors in Donald Trump’s successful captureof the Republican Party prior to the 2016general election.5 Indeed, once nationalistbeliefs are accounted for, few of the stan-dard sociodemographic predictors of votingpreferences reach statistical significance (seeAppendix C).

Do these patterns hold when Trump sup-port is compared to support for Ted Cruz?Given the similarities between the two cam-paigns’ rhetoric, we hypothesized that na-tionalist attitudes would not be an impor-tant distinguishing factor between Trumpand Cruz supporters. Indeed, as the thirdpanel of Figure 4 illustrates, we find no sig-nificant relationships between nationalismand vote choice when comparing support forthese two candidates. Given the small sam-ple size (N = 135) and resulting large stan-dard errors, particularly in the full model,we hesitate to draw conclusive inferencesfrom these results. Nonetheless, they doprovide suggestive evidence in favor of Hy-pothesis 4.

Finally, we turn to our last cross-sectional analysis, comparing Clinton andSanders support in the Democratic primary.We predicted that Sanders’ reluctance to en-gage with identity-based appeals, and na-tionalist rhetoric in particular, along withhis populism, should make it more likely forhim than for Clinton to draw support fromnationally disengaged voters (H5). The re-sults are presented in the fourth panel ofFigure 4. As expected, disengagement fromthe nation is consistently associated with re-

5It is important to keep in mind that the dependent variable is based on retrospective accounts of primaryvoting behavior, so our estimates are likely to overestimate Trump support, making our analysis conservative.

19

spondents’ recall of having voted for Sandersover Clinton. Interestingly, we also observea significant difference between creedal andardent nationalism, which had not been an-ticipated by our hypotheses: among respon-dents with high levels of pride in the na-tion, those who adhere to exclusionary con-ceptions of national membership were morelikely to support Clinton than Sanders, evennet of sociodemographic controls.6

6.3 Did Trump Ride a Na-tivist Wave?

The cross-sectional analyses confirmed thatnationalism played a crucial role in the 2016presidential election. Restrictive and ar-dent nationalists were more likely to supportTrump over moderate candidates in the Re-publican primary and over Clinton in thegeneral election, while the disengaged weremore likely to support Sanders over Clintonin the Democratic primary. Most of theseassociations held even when partisan iden-tification was included in the models. Butwhy was an ethno-nationalist populist ableto capture the Republican Party and thepresidency in 2016 and not in prior elec-tions? Were the mid-2010s characterizedby a sudden surge in exclusionary nation-alism and a drop in national pride acrossthe U.S. population? Or were other tem-poral trends—such as partisan sorting (Bal-dassarri and Gelman 2008)—more relevantfor explaining the increased importance ofnationalism in the 2016 election?

These questions led us to posit two tem-poral hypotheses: that exclusionary forms

of nationalism have been rising in generalprevalence in the United States (H6) andthat restrictive and ardent nationalism havebecome increasingly overrepresented amongRepublicans, while creedal nationalism anddisengagement from the nation have be-come increasingly overrepresented amongDemocrats (H7). In principle, these twoscenarios may be independent of one an-other: it is possible that both are true or,alternatively, that only one is true. Whileboth might also be false, it is unlikely thatthe Trump election, which marked a radicalchange in American politics, emerged out ofa period of absolute stability in public opin-ion.

In testing these predictions, we usecross-sectional data collected in 1996, 2004,2012, and 2016 to identify long-term trendsin the distribution of the four nationalismtypes, both in the aggregate and across thetwo parties. The aggregate results are pre-sented in Figure 5. The x-axis representstime, while the y-axis indicates the rela-tive proportion of the nationalism classes—visualized with the four trend lines—in eachsurvey year.

The patterns in the top panel of Figure5, which plots the distribution of classes overtime for all respondents, are at odds withHypothesis 6. While there has been a smallsecular increase in ardent nationalism be-tween 1996 and 2016, restrictive nationalismreached a peak at 44 percent of the samplein the aftermath of the September 11th at-tacks and has been steadily declining since,to less than 25 percent of the sample in 2016(down from 32 percent in 1996). Creedal na-tionalism remains at a similar level in 2016

6Among the controls, Clinton supporters were more likely to be African American, have either low oradvanced education, and live in the Northeast (compared to the Mountain West). Given Sanders’ welldocumented difficulties of appealing to minority voters, the race results have considerable face validity.

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(36 percent)to what it was in 1996 (38 per-cent), having recovered from its 2004 lowof 18 percent of the sample. Finally, disen-gagement from the nation has increased inrecent years from a low of 10 percent in 1996to a high of nearly 18 percent in 2016.

Together these results demonstrate thatstrong nationalist attitudes in general—andtheir exclusionary varieties in particular—have been in decline over the past twentyyears. This trend was temporarily re-versed in the aftermath of 9/11, when ar-dent and restrictive nationalism increasedsharply and overtook creedal nationalism asdominant orientations toward the nation,but this change was short-lived: by 2012,the distribution of nationalist beliefs lookedremarkably similar to 1996, with the excep-tion of growing disengagement with te na-tion. The 2016 election, therefore, did notoccur in the context of a pronounced spikein the types of nationalism that fueled Don-ald Trump’s support in the primary andgeneral election. It appears that the rela-tive salience of pre-existing attitudes—andpossibly their changing distribution acrossparties—holds more promise for explain-ing the timing of Donald Trump’s victorythan do aggregate shifts in public opinion(Bonikowski 2017).

One possible objection to this conclu-sion is that the above analysis includes eth-nic and racial minorities, who are less likelyto espouse exclusionary forms of national-ism. Would the downward trend in nation-alism be absent among whites? the bottompanel in Figure 5, which reports the dis-tribution of nationalist classes among thewhite subsample, suggests otherwise. Themain differences between the two graphs area higher prevalence of ardent and restric-tive nationalism among whites in 2004, a

less steep decline in restrictive nationalismamong whites between 2012 and 2016, and asharper increase in creedal nationalism be-tween 2012 and 2016 in the sample as awhole. That aside, many of the same pat-terns hold in both figures: since 9/11, re-strictive and ardent nationalism has beendeclining, while creedal nationalism and dis-engagement with the nation has been grow-ing. There is little evidence of an ethno-nationalist surge in the prelude to the 2016election.

Even though ethno-nationalism has beendeclining in the general population, it is pos-sible that at the same time, the four types ofnationalism have become increasingly sortedbetween the two national parties, as pre-dicted in Hypothesis 7. Figure 6 presentstrends in the distribution of nationalist be-liefs broken down by partisan identification.These results differ sharply from what weobserved in the sample as a whole: insteadof relative stability, there is a sharp diver-gence in nationalism over time, both withinand across parties.

These patterns are clearest amongstrong partisans. Whereas in 1996, re-strictive nationalism was common amongstrong Democrats (at 23 percent, just be-low creedal and ardent nationalism), by2016 it was the least prevalent form of na-tionalism in this group, found only among8 percent of strong Democratic partisans.Over the same time period, creedal nation-alism increased dramatically among strongDemocrats, from 32 percent in 1996 to 50percent in 2016. Among strong Republi-cans, the opposite was true: restrictive na-tionalism increased between 1996 and 2016from 38 to 48 percent, while creedal na-tionalism declined precipitously, from 32 to9 percent. Similar, though more muted,

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patterns are present among less stronglycommitted Democratic and Republican par-tisans: an increase in creedal national-ism and decrease in restrictive nationalismamong Democrats and an increase in ethno-nationalism (especially its ardent variety)and a decrease in creedal nationalism amongRepublicans.7

What these temporal trends clearly re-veal is that nationalism has been increas-ingly sorted by party in the United States.In 1996, it would have been difficult topredict a respondent’s partisan identitybased on his or her nationalist beliefs (andvice versa), whereas by 2016, partisanshipand nationalism had become tightly cou-pled: Republicans had become predomi-nantly ethno-nationalist and Democrats hadbecome overwhelmingly committed to inclu-sive nationalism.

To more formally capture the partisansorting process, we calculate lambda coef-ficients for each wave of the data. Thesemeasures of association between categori-cal variables are comparable across sam-ples, unlike unstandardized measures likeChi-squared. The results are presented inFigure 7; higher lambda values correspondto stronger association between party iden-tification and nationalism in a given year.The two trend lines correspond to two typesof comparison: (1) between all four vari-eties of nationalism and weak/strong Demo-cratic/Republican identification and (2) be-tween exclusive/inclusive nationalism (i.e.,creedal and disengaged classes on one handand ardent and restrictive on the other) andweak/strong Democratic/Republican iden-tification.

Consistently with the patterns observedin Figure 6, the association between the fourtypes of nationalism and party increasesdramatically over the span of our data,from 0.004 to 0.097, with the largest rel-ative change occurring between 1996 and2004 and the trend stabilizing after 2012.This further confirms that nationalism hasbecome increasingly predictive of partisanidentification (and vice versa). This tem-poral comparison, however, treats all fournationalism types as equivalent, whereasour interest is specifically in the polariza-tion of exclusive and inclusive nationalism.The second trend line in Figure 6 capturesthis distinction. Here, the pattern is evenstarker: partisan sorting has been increas-ing sharply and steadily between 2004 and2016, reaching a peak of 0.1841 in the latteryear.

These results demonstrate that by 2016,Democrats and Republicans were sharplydivided in their understanding of the na-tion, with Republican overwhelmingly fa-voring ethno-nationalist conceptions of na-tional belonging. This was not a sud-den change, however, but one that hadbeen gradually building over the prior twodecades, and particularly since the after-math of the September 11 attacks. It ap-pears then that Donald Trump did not cat-alyze a major shift in the political relevanceof American nationalism, but rather capi-talized on a demand for ethno-nationalistpolitics that had long been growing amongRepublican voters.

7Although we did not formulate hypotheses for independents, the temporal patterns among them arestriking, with a moderate decrease in restrictive and creedal nationalism offset by a major increase in disen-gagement (from 16 to 26 percent).

24

●

●

●

●

●

●

●

●

0.0

0.1

0.2

0.3

1995 2000 2005 2010 2015

Year

Goo

dman

and

Kru

skal

's la

mbd

a

Nationalism types: ● ●All Inclusive vs. Exclusive

Figure 7: Association between Party and Nationalism Type, 1996-2016

7 Discussion and Con-

clusion

This study has used a unique combina-tion of computational text analysis and pri-mary and secondary survey data to exam-ine the relationship between multiple formsof American nationalism and voting pref-erences in the 2016 presidential election.Our cross-sectional analysis has demon-strated that exclusionary forms of nation-alism provided a crucial base of supportfor Donald Trump, both during the Re-publican primary and the general election.The latter results held even once parti-san identification—the strongest predictorof vote choice—was taken into account.Ethnic exclusion, however, wasn’t the onlyrelevant aspect of nationalism in the 2016election. Varieties of nationalism charac-terized by low levels of national pride (i.e.,restrictive nationalism and disengagement

form the nation), were highly predictive ofsupport for Trump over Clinton, and dis-engagement from the nation was associatedwith a preference for Sanders over Clintonin the Democratic primary.

As our longitudinal analysis demon-strates, the importance of nationalism inthe 2016 election did not result from a sud-den surge in nationalist beliefs among theU.S. electorate. On the contrary, popularconceptions of nationhood, on average, havebeen either stable or have become increas-ingly inclusive (though the immediate after-math of 9/11 marked a temporary deviationfrom this trend). This does not imply, how-ever, that public opinion trends were irrele-vant for Donald Trump’s success. What ouranalysis reveals is that between 1996 and2016, Americans’ nationalist beliefs have be-come increasingly mapped onto their parti-san identities. By 2016, most Republicansadhered to restrictive or ardent nationalism,while most Democrats espoused creedal na-

25

tionalist beliefs. The sorting of national-ism by party represents a marked differencefrom the configuration of nationalist beliefsin 1996, the first wave of our data, when na-tionalist cleavages were largely cross-cuttingacross parties.

In identifying these empirical patterns,this study makes four primary contributionsto the sociology and political science liter-ature on radical politics and nationalism.First, it sets aside the vague category of”cultural” sources of radical-right supportand offers a more theoretically precise andempirically grounded framework for under-standing the common source of antipathytoward both native- and foreign-born eth-nic, racial, and religious minorities, as wellas of skepticism toward established institu-tions and elites. These seemingly disparatesentiments are rooted in fundamental beliefsabout the meaning of one’s own nationalidentity. Sharp distinctions in collectiveself-understanding constitute cultural cleav-ages in a national population that may belatent much of the time, but under particu-lar circumstances can guide people’s politi-cal decisions. The 2016 presidential electionwas clearly one such moment. In additionto a variety of structural changes that mayhave increased the resonance of distinct na-tionalist appeals, the partisan sorting of—but not aggregate increase in—nationalistbeliefs appears to have been an importantcontributing factor.

Second, by relating the discursive strate-gies of the various campaigns in the 2016election to the cultural schemas held by vot-ers, the paper draws attention to the impor-tance of bringing together the supply anddemand sides of politics. The computa-tional text analysis of campaign speeches,combined with our reading of the secondary

literature, enabled us to posit a series of hy-potheses about the likely sources of supportfor the various candidates. As our analy-ses reveal, in 2016, when identity concernsappear to have been crucial, campaign’s de-cisions to rely on a particular forms of na-tionalist appeals—or to sidestep national-ism altogether—had important implicationsfor respondents’ evaluations of the candi-dates. While the ultimate outcomes of theprimary and general elections were likely afunction of a host of causal factors, both in-stitutional and symbolic, it is likely that therelative resonance of various forms of na-tionalist claims-making played an importantrole in the process.

Third, by exploring questions related topolarization, we have demonstrated that na-tionalism represents yet another belief do-main that has become increasingly sortedby party in the recent decades. Given thecultural importance of nationalist beliefs,however, we view this trend as particularlyconcerning. Cultural schemas of the nationare not merely an isolated social attitude orpolicy preference; they are one of the mas-ter frames that organizes people’s collectiveself-understanding, shapes their dispositiontoward other groups, affects their evaluationof the nation’s past and future trajectories,and may impact the structure and contentof interpersonal interactions. When thesecultural rifts become mutually reinforcingvis-a-vis other sociodemographic and politi-cal cleavages, they are likely to further con-tribute to the erosion of social solidarity anddemocratic consensus-building, with poten-tially deleterious consequences for long-termpolitical stability. To put things more con-cretely, the fact that one of the two na-tional parties has become a party of ethno-nationalist exclusion is unlikely to produce a

26

stable democratic equilibrium, particularlyin the context of rapidly rising elite polariza-tion, mass negative partisanship, and grow-ing demographic diversity.

Fourth, our temporal analysis demon-strates that the partisan sorting of nation-alist beliefs did not occur in the immedi-ate prelude to the 2016 election. On thecontrary, it was a product of a long-termprocess that appears to have begun in theaftermath of the September 11th attacksand continued largely unabated for the sub-sequent decade and a half. This suggeststhat symbolic crises may be more importantin producing changes in nationalist beliefsthan structural shocks, such as the GreatRecession. Although the George W. Bushadministration sought to unite the nationafter 9/11 and prevent the attack from gen-erating excessive inter-group tensions, thechoice to treat the event as an unprece-dented national security crisis rather than acrime, the concomitant radicalization of po-litical discourse related to Islam and Mus-lims (Bail 2014), and the subsequent dou-bling down of Republican political elites onwhite identity politics (Bonikowski 2019)appear to have had long-term consequences.

In light of these trends, it makes moresense to view the Trump campaign and pres-idency as products of underlying crescivechanges in U.S. political culture, rather thanas causes in themselves of the country’s turntoward right-wing radicalism. Over the pastten years, the demand for radical-right pol-itics, characterized by ethno-nationalist ex-clusion, a moral critique of political elites,and nostalgia for the nation’s past glory,has been steadily growing among Republi-cans. This helps explain Republican vot-ers’ support for Sarah Palin vice presiden-tial candidacy in the 2008 election and for

the Tea Party’s public protests and electoralactivism in the early 2010s. Neither of thesepolitical projects, however, was able to givevoice to, empower, and mobilize the growingardent- and restrictive-nationalist Republi-can voting block with the same degree ofefficacy as Donald Trump. It is by skillfullyarticulating and amplifying the nationalistgrievances of a growing majority of Repub-licans that Trump was able to capture theRepublican Party and ultimately the presi-dency.

Finally, this paper demonstrates thevalue of bridging the divide between po-litical science and sociology in the studyof radical politics. By synthesizing in-sights on the conceptualization and mea-surement of belief structures from culturalsociology and the role of conflicting nation-hood schemas from the nationalism litera-ture with the focal subject matter of com-parative party politics scholarship, we havesought to make contributions to both disci-plines. We hope that our work will inspirepolitical sociologists to continue their re-engagement with the study of institutionalpolitics, while prompting political scientiststo take culture more seriously in their re-search on electoral outcomes. The areasof commonality between these historicallyrelated fields are expanding and our workis both inspired by and seeks to fuel thecontinued cross-pollination of ideas betweenthem. The value of such engagement is notpurely academic: the dangers posed to thefuture of democracy by the rise of radicalpolitics demand rigorous, multicausal anal-yses that transcend disciplinary limitations.It is our view that nationalism—clearly the-orized and precisely measured—belongs atthe center of such analyses.

27

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Appendices

A Latent Class Analysis Model Selection

This is the LCA appendix.

B Results of Regressions of Voting Preferences on Na-

tionalism Variables and Covariates

31

Tab

le2:

Log

isti

cre

gres

sion

ofvo

tech

oice

onnat

ional

ism

clas

ses

Tru

mp

vs.

Clinto

nClinto

nvs.

Sanders

Tru

mp

vs.

Cru

zTru

mp

vs.

Modera

tes

Bas

elin

eSoc

Dem

Full

Bas

elin

eSoc

Dem

Bas

elin

eSoc

Dem

Bas

elin

eSoc

Dem

Cre

edal

Ref

Ref

Ref

Ref

Ref

Ref

Ref

Ref

Ref

Res

tric

tive

2.68

30∗∗

∗2.

170∗

∗∗0.

885∗

0.72

30.

350.

675

1.12

22.

603∗

∗∗2.

642∗

(0.3

38)

(0.3

55)

(0.3

83)

(0.4

83)

(0.5

52)

(0.6

75)

(0.8

70)

(0.6

56)

(1.1

93)

Ard

ent

1.80

9∗∗∗

1.73

8∗∗∗

1.59

5∗∗∗

1.21

5∗∗

0.98

50.

554

0.75

41.

984∗

∗∗2.

154∗

(0.2

92)

(0.3

48)

(0.4

73)

(0.4

09)

(0.5

11)

(0.6

27)

(0.6

82)

(0.5

76)

(1.0

05)

Dis

enga

ged

1.21

1∗∗

1.80

8∗∗∗

1.42

3∗∗

-0.9

06∗

-1.7

05∗∗

0.12

51.

622

1.39

51.

628

(0.3

76)

(0.4

49)

(0.4

75)

(0.4

17)

(0.5

84)

(1.0

38)

(2.1

99)

(0.9

12)

(1.1

99)

Whit

eR

efR

efR

efR

efR

ef

Bla

ck-2

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∗∗∗

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952.

147∗

∗∗-2

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74(0

.451

)(0

.613

)(0

.625

)(1

.597

)(1

.836

)

His

pan

ic-1

.117

4∗∗

-1.0

94-0

.161

-0.1

35-0

.602

(0.4

23)

(0.5

74)

(0.5

38)

(1.1

25)

(0.7

50)

Oth

er-0

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-0.0

54-0

.421

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77-1

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(0.5

46)

(0.7

41)

(0.8

56)

(1.1

40)

(0.9

57)

Les

sth

anH

SR

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efR

efR

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me

colleg

e1.

7028

∗1.

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*1.

165

-1.4

51.

(0.6

97)

(0.5

65)

(0.9

92)

(1.2

52)

(1.6

39)

BA

1.33

1.89

4∗-2

.451

∗1.

986

-1.9

01(0

.764

)(0

.565

)(1

.068

)(1

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)(1

.715

)

Adva

nce

ddeg

ree

0.55

80.

724

-0.8

011.

608

-1.7

13

32

Table

2co

ntinued

from

previouspage

(0.8

17)

(0.8

28)

(1.1

75)

(1.3

83)

(1.6

86)

Nor

thea

stR

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wes

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(0.3

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35)

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(0.3

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(0.4

69)

(0.5

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(0.7

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nta

in-0

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2-0

.688

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37∗

-0.9

301.

133

(0.4

422)

(0.6

27)

(0.6

19)

(1.3

56)

(1.4

65)

Pac

ific

-1.5

02∗∗

∗-1

.705

∗∗-0

.290

-1.3

560.

02(0

.397

1)(0

.627

)(0

.620

)(1

.047

)(0

.948

)

Pro

test

ant

Ref

Ref

Ref

Ref

Ref

Rom

anC

athol

ic-0

.885

4∗-0

.823

*0.

985

1.20

30.

383

(0.3

19)

(0.3

99)

(0.5

55)

(0.6

92)

(0.6

59)

Jew

ish

-7.8

62∗∗

∗-8

.692

∗∗∗

0.17

1-5

.413

∗-6

.046

∗∗

(0.8

04)

(1.3

79)

(0.9

28)

(2.2

22)

(2.3

03)

Oth

er-0

.582

-0.6

01-0

.145

-0.1

56-0

.802

(0.4

02)

(0.4

98)

(0.5

16)

(0.7

44)

(0.8

00)

Non

e-1

.007

∗∗-1

.018

∗-0

.286

0.89

11.

126

(0.3

33)

(0.4

49)

(0.5

83)

(0.8

43)

(0.7

74)

Rel

igio

sity

0.32

420.

260

0.25

50.

325

1.29

4∗

(0.2

73)

(0.3

52)

(0.4

63)

(0.5

88)

(0.5

25)

Not

Bor

nin

US

0.24

0-0

.614

0.94

6-0

.111

-1.1

83(0

.353

3)(0

.409

)(0

.555

)(0

.891

)(0

.642

)

Mal

e-0

.237

-0.9

760.

244

0.04

6-2

.173

∗∗

(0.2

24)

(0.3

22)

(0.3

37)

(0.5

31)

(0.6

81)

Age

0.01

30.

029∗

∗-0

.004

0.01

50.

030∗

33

Table

2co

ntinued

from

previouspage

(0.0

07)

(0.0

09)

(0.0

10)

(0.0

15)

(0.0

14)

Inco

me

(200

4)0.

420∗

∗0.

411∗

-0.0

66-0

.104

0.15

9(0

.131

)(0

.164

)(0

.191

)(0

.369

)(0

.331

)

Str

ong

Dem

ocr

atR

efR

efR

efR

ef

Dem

ocr

at2.

138∗

∗∗

(0.6

38)

Indep

enden

t4.

350∗

∗∗

(0.7

41)

Rep

ublica

n6.

064∗

∗∗

(0.7

33)

Str

ong

Rep

ublica

n6.

884∗

∗∗

(0.7

62)

Con

stan

t-1

.740

∗∗∗

-6.6

34∗∗

∗-1

0.29

3∗∗∗

0.28

93.

094

0.30

3-0

.107

-1.3

22∗∗

-2.3

46(0

.243

)(1

.468

)(2

.167

)(0

.197

)(2

.270

)(0

.545

)(4

.247

)(0

.494

)(4

.352

)N

631

562

552

267

249

141

119

166

146

BIC

2496

.95

2208

.172

219

49.8

423

1035

.815

310

12.6

587

525.

2048

517.

8484

643.

4693

628.

1966

Exp

onen

tiat

edco

effici

ents

;st

andar

der

rors

inpar

enth

eses

∗p<

0.05

,∗∗

p<

0.01

,∗∗

∗p<

0.00

1

34

C Sociodemographic Predictors of Class Membership

Table 3: Conditional Probabilities of Class Membership by Sociodemographic Attributes

Creedal Disengaged Restrictive Ardent P -Value

Class prevalence 0.36 0.15 0.25 0.25

White 0.33 0.13 0.32 0.23 0.000Black 0.42 0.28 0.12 0.18Hispanic 0.32 0.15 0.10 0.43Other 0.60 0.15 0.12 0.13

Less than HS 0.41 0.00 0.26 0.34 0.000HS or some college 0.31 0.17 0.27 0.25Bachelor’s degree 0.41 0.12 0.20 0.27Advanced degree 0.63 0.11 0.14 0.13

Lives in Northeast 0.33 0.23 0.22 0.21 0.270Lives in Midwest 0.36 0.18 0.22 0.24Lives in South 0.36 0.13 0.27 0.25Lives in Mountain 0.39 0.02 0.22 0.37Lives in Pacific 0.36 0.15 0.26 0.23

Protestant 0.22 0.12 0.37 0.30 0.000Roman Catholic 0.26 0.06 0.29 0.39Jewish 0.48 0.24 0.00 0.28Other 0.53 0.16 0.25 0.06None 0.44 0.25 0.11 0.19

Not Strongly Religious 0.46 0.15 0.18 0.21 0.000Strongly Religious 0.22 0.14 0.34 0.29

Female 0.37 0.17 0.29 0.17 0.000Male 0.34 0.13 0.20 0.32

Born in US 0.36 0.12 0.30 0.22 0.000Not born in US 0.36 0.24 0.08 0.31

Mean age 43.74 39.36 47.80 51.81 0.000

Mean income (2004 dollars) $36,887 $38,985 $47,635 $33,544 0.000

Strong Democrat 0.53 0.14 0.08 0.25 0.000Democrat 0.54 0.11 0.16 0.19Independent 0.27 0.27 0.27 0.20Republican 0.23 0.08 0.39 0.30Strong Republican 0.14 0.15 0.39 0.33

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